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morph-v3-large

⚡ API で実行

Morph V3 Large is Morph’s high-accuracy apply model for complex code edits. Prompts follow a fixed format with <instruction>, <code> and <update> sections.

料金: 入力:100 万トークンあたり 216 クレジット(約 $1.08)、出力:100 万トークンあたり 456 クレジット(約 $2.28)。

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Morph V3 Large の使い方ガイド

Morph V3 Large API on ModelFold

Morph V3 Large is Morph’s high-accuracy apply model for complex code edits. Prompts follow a fixed format with <instruction>, <code> and <update> sections. Try Morph V3 Large in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.

What Is the Morph V3 Large API

Morph V3 Large at a glance

Morph V3 Large is a chat model from Morph. It accepts text as input and returns text, with a context window of up to 262K tokens.

Use it without hosting anything

On ModelFold you call Morph V3 Large with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.

Core Capabilities of Morph V3 Large

Up to 262K tokens of context

Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.

Structured outputs

Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.

How to Use Morph V3 Large on ModelFold

  1. 1

    Step 1: Try it in the Playground

    Open the Playground at the top of this page, type a prompt and see how Morph V3 Large responds before writing any code.

  2. 2

    Step 2: Create an API key

    Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.

  3. 3

    Step 3: Send a request

    Call POST https://modelfold.ai/v1/chat/completions with "model": "morph-v3-large" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.

  4. ✓

    Step 4: Ship and monitor

    Integrate the response into your product and check token usage and spend for every call in the console logs.

What You Can Build with Morph V3 Large

AI coding assistants

Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.

Tool-calling backends

Route requests, call functions and chain API calls as the worker model inside larger agent systems.

Low-latency experiences

Power chat interfaces, autocomplete and interactive tools where users expect fast responses.

Frequently Asked Questions

What is Morph V3 Large?⌄

Morph V3 Large is Morph’s high-accuracy apply model for complex code edits. Prompts follow a fixed format with <instruction>, <code> and <update> sections.

Which inputs does Morph V3 Large support?⌄

Morph V3 Large accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.

How long is the context window of Morph V3 Large?⌄

Up to 262K tokens, shared between your input and the model’s output.

Does Morph V3 Large support function calling?⌄

Function calling is not listed for Morph V3 Large; requests that include tools will be rejected. Use plain prompts or JSON output instead.

How is Morph V3 Large billed on ModelFold?⌄

Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.

How do I call Morph V3 Large through the API?⌄

Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "morph-v3-large", using your ModelFold API key as the Bearer token.

料金表
入力216 クレジット 1M tokens≈ $1.08
出力456 クレジット 1M tokens≈ $2.28

トークン単位で課金し、入力と出力は別料金です。思考トークンは出力に含まれます。Playground でも同じ計算を使います。

API ドキュメントを見る →AI Agents · Claude Code / Cursor / Trae →
クイックスタート
POST/v1/chat/completions
curl https://modelfold.ai/v1/chat/completions \
  -H "Authorization: Bearer $MODELFOLD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"morph-v3-large","messages":[{"role":"user","content":"Hello"}]}'